Genetic parameters of the fatty acid composition of milk of Canadian holsteins and genetic associations between feed intake and type traits in Canadian holsteins
Bibliographic record
Abstract
The first part of the thesis discusses about the fatty acid composition of bovine milk fat. One morning milk sample was collected from each of 3185 dairy cows between February and June 2010 from 52 commercial herds enrolled in the Quebec Dairy Production Centre of Expertise, Valacta. Individual fatty acid percentages (g/100g of total fatty acids) were determined for each sample by gas chromatography. After necessary editing, final data included 2573 cows representing 46 herds. The objectives of the first study were to study the effects of parity, age at calving and stage of lactation on fatty acid composition of milk of Canadian Holsteins. The model included the fixed effects of parity, age at calving and stage of lactation nested within parity and random effects of herd-year-season of calving and residual. The mixed model was fitted using restricted maximum likelihood (REML) methodology. Parity of cow was significantly (P < 0.05) related to the variation in most fatty acids in milk fat. First parity cows had relatively higher proportions of some beneficial fatty acids and lower proportions of potentially harmful saturated fatty acids as compared to later parity cows. Stage of lactation significantly affected fatty acid composition of cows. The short and medium chain fatty acids were low in the beginning of lactation and increased during the early part of lactation, whereas, an opposite trend was observed for long chain fatty acids. The objective of the second study was to estimate heritabilities of and genetic and phenotypic correlations among fatty acids in milk of Canadian Holsteins using fatty acid data from the first study. Genetic parameters were estimated using multitrait animal models fitted under REML. The estimates of heritability ranged from 0.01 to 0.39 with standard errors ranging from 0.01 to 0.06. Generally, monounsaturated (0.20 to 0.39) and saturated fatty acids (0.02 to 0.34) showed higher heritability estimates than polyunsaturated fatty acids (0.01 to 0.21) and trans fatty acids (0.01 to 0.05). Overall, saturated fatty acids were negatively genetically correlated with monounsaturated and polyunsaturated fatty acids. Most of the genetic correlation estimates between monounsaturated and polyunsaturated fatty acids were positive. In order to change milk fat composition in a desirable direction, selection for one or more monounsaturated fatty acids may be more effective than selection against saturated fatty acids.The objective of the third study (Part 2 of thesis) was to estimate genetic correlations between feed intake and type traits with a view to considering the potential of indirect genetic selection for feed intake using type traits in dairy cattle. Feed intake data on 119388 first lactation Holstein cows were obtained from the Quebec Dairy Production Centre of Expertise, Valacta. The two trait animal models were fitted under restricted maximum likelihood (REML). Estimates of heritabilities ± standard errors for DMI, NELI and CPI were 0.12 ± 0.01, 0.13 ± 0.01 and 0.13 ± 0.01, respectively. Estimates of heritabilities ± standard errors of dairy strength, angularity, body depth, stature and final score were 0.31 ± 0.01, 0.24 ± 0.01, 0.30 ± 0.01, 0.50 ± 0.01 and 0.22 ± 0.01, respectively. All phenotypic and genetic correlation estimates between feed intake and type traits were positive. Angularity showed the highest genetic correlation estimates with feed intake traits (0.60 to 0.65) followed by dairy strength (0.48 to 0.54), stature and body depth (0.29 to 0.36) with all three feed intake traits. Angularity, dairy strength, stature and body depth may be useful for indirect selection of feed intake traits in dairy cattle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".